B. M. Herbst
- Statistical and Nonlinear Physics top 0.5%
- Numerical Analysis top 1%
- Atomic and Molecular Physics, and Optics top 10%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Co-authors
- Mark J. AblowitzJ. A. C. WeidemanC. M. SchoberJohan A. du PreezR. G. HalburdA. R. MitchellJ. Ll. MorrisChris Aldrich
- Topics
- Nonlinear Waves and Solitons (21 papers)Nonlinear Photonic Systems (18 papers)Numerical methods for differential equations (17 papers)
- Journals
- Physical Review LettersIEEE Transactions on Pattern Analysis and Machine IntelligenceJournal of Computational Physics
- Partner nations
- South AfricaUnited StatesUnited Kingdom
In The Last Decade
B. M. Herbst
51 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 87
- Statistical and Nonlinear Physics 825
- Numerical Analysis 455
- Atomic and Molecular Physics, and Optics 317
- Computer Vision and Pattern Recognition 222
- Electrical and Electronic Engineering 196
Countries citing papers authored by B. M. Herbst
This map shows the geographic impact of B. M. Herbst's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by B. M. Herbst with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites B. M. Herbst more than expected).
Fields of papers citing papers by B. M. Herbst
This network shows the impact of papers produced by B. M. Herbst. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by B. M. Herbst. The network helps show where B. M. Herbst may publish in the future.
Co-authorship network of co-authors of B. M. Herbst
This figure shows the co-authorship network connecting the top 25 collaborators of B. M. Herbst. A scholar is included among the top collaborators of B. M. Herbst based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with B. M. Herbst. B. M. Herbst is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | Off-line signature verification: A comparison between human and machine performance | 17 |
| 3 | 31 | |
| 4 | 5 | |
| 5 | 5 | |
| 6 | 164 | |
| 7 | 3 | |
| 8 | 27 | |
| 9 | 30 | |
| 10 | 25 | |
| 11 | 19 | |
| 12 | 120 | |
| 13 | 3 | |
| 14 | 5 | |
| 15 | 3 | |
| 16 | 9 | |
| 17 | 280 | |
| 18 | 27 | |
| 19 | 51 | |
| 20 | 5 |
About B. M. Herbst
B. M. Herbst is a scholar working on Numerical Analysis, Statistical and Nonlinear Physics and Computer Vision and Pattern Recognition, having authored 54 papers that have together received 1.7k indexed citations. Recurring topics across this work include Nonlinear Waves and Solitons (21 papers), Nonlinear Photonic Systems (18 papers) and Numerical methods for differential equations (17 papers). The work is most often cited by research in Numerical Analysis (455 citations), Statistical and Nonlinear Physics (825 citations) and Modeling and Simulation (143 citations). B. M. Herbst has collaborated with scholars based in South Africa, United States and United Kingdom. Frequent co-authors include Mark J. Ablowitz, J. A. C. Weideman, C. M. Schober, Johan A. du Preez, R. G. Halburd, A. R. Mitchell, J. Ll. Morris, Chris Aldrich, Lidia Auret and John T. McCoy. Their work appears in journals such as Physical Review Letters, IEEE Transactions on Pattern Analysis and Machine Intelligence and Journal of Computational Physics.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.